SAP Business Data Cloud

An Introduction
1. Auflage 2027
ISBN: 978-1-4932-2867-6
Verlag: Rheinwerk Verlag GmbH

Buch, Englisch, 375 Seiten, Format (B × H): 178 mm x 254 mm

Consolidate your fragmented data landscape with SAP Business Data Cloud! Understand the architecture and semantic foundation of this new solution and walk through onboarding, system formation, and initial activation. Data products are at the core of SAP Business Data Cloud, so get to know what they are and what they do. Then explore data and semantic modeling with SAP Datasphere, advanced data engineering with SAP Databricks, and analytics with SAP Analytics Cloud. From connecting to your existing SAP BW system to implementing intelligent applications, this guide will show you all that SAP Business Data Cloud can do.

Highlights include:

1) Architecture

2) Onboarding

3) System formation

4) Data products

5) SAP Datasphere

6) SAP Databricks

7) SAP Analytic Cloud

8) SAP Business Warehouse (SAP BW)

9) Intelligent applications

10) Governance

Autoren/Hrsg.

Bobbili, Geetha Madhuri

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Mathematik | Informatik EDV | Informatik Business Application Unternehmenssoftware SAP
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse

Inhaltsverzeichnis

... Preface ... 15

... Target Audience ... 16

... Objective of This Book ... 16

... How to Read This Book ... 17

... Acknowledgments ... 19

1 ... What Is SAP Business Data Cloud? ... 21

1.1 ... The Evolution of Enterprise Data: From Silos to Unified Data Fabrics ... 22

1.2 ... Why Traditional Data Extraction Loses Business Context and Trust ... 25

1.3 ... Modern Enterprise Data Requirements and Architectural Challenges ... 29

1.4 ... SAP Business Data Cloud: Evolution of the Business Data Fabric ... 31

1.5 ... Core Value Pillars of SAP Business Data Cloud ... 34

1.6 ... Key Personas and Roles in SAP Business Data Cloud ... 37

1.7 ... Positioning SAP Business Data Cloud Within SAP’s Data, Analytics, and AI Strategy ... 40

1.8 ... Summary ... 42

2 ... Architectural Overview and the Semantic Foundation ... 43

2.1 ... The Architectural Framework: Source-to-Business-Insight Data Flow ... 44

2.2 ... Key Components of SAP Business Data Cloud Architecture ... 48

2.3 ... Foundation Services for Data Ingestion, Harmonization, and Data Products ... 66

2.4 ... End-to-End Banking Transformation Scenario with SAP Business Data Cloud ... 69

2.5 ... Summary ... 75

3 ... Getting Started with Onboarding and System Formation ... 77

3.1 ... Onboarding Concepts ... 77

3.2 ... Provisioning ... 82

3.3 ... System Formation and Tenant Wiring ... 92

3.4 ... Tenant Rewiring ... 96

3.5 ... SAP Business Data Cloud Cockpit as the Control Plane ... 99

3.6 ... Activation of SAP-Managed Content ... 103

3.7 ... Summary ... 105

4 ... Understanding Data Products in SAP Business Data Cloud ... 107

4.1 ... Introduction to Data Products ... 108

4.2 ... Core Architecture of Data Products ... 112

4.3 ... Metadata and Semantic Foundations ... 119

4.4 ... Types of Data Products ... 122

4.5 ... Data Product Discovery, Ownership, and Consumption ... 136

4.6 ... Data Democratization and Marketplace-Driven Data Consumption ... 142

4.7 ... Data Products for Analytics and AI ... 145

4.8 ... Summary ... 149

5 ... Data and Semantic Modeling with SAP Datasphere ... 151

5.1 ... SAP Datasphere as the Foundation of a Business Data Fabric ... 152

5.2 ... Role of SAP Datasphere in SAP Business Data Cloud ... 153

5.3 ... Architectural Positioning ... 154

5.4 ... Architectural Building Blocks of SAP Datasphere ... 156

5.5 ... Data Builder: Technical Data Modeling ... 174

5.6 ... Business Builder: Semantic Business Modeling ... 182

5.7 ... Data Sharing Cockpit: Central Hub for Data Provider Management ... 186

5.8 ... Business Scenario: Financial Performance Analysis Using Harmonized Data Products ... 198

5.9 ... Summary ... 200

6 ... Advanced Data Engineering and AI/ML with SAP Databricks ... 201

6.1 ... Role of SAP Databricks in SAP Business Data Cloud ... 201

6.2 ... Architectural Integration ... 203

6.3 ... Zero-Copy Data Access and Bidirectional Data Sharing ... 206

6.4 ... SAP Business Data Cloud Connect and the Open Data Ecosystem ... 210

6.5 ... Data Engineering and AI Capabilities ... 221

6.6 ... Design Considerations and Best Practices ... 226

6.7 ... Business Scenario: Enriching an SAP Data Product with AI Insights ... 228

6.8 ... Summary ... 238

7 ... Modernizing SAP BW with SAP Business Data Cloud ... 239

7.1 ... The Evolution of SAP BW: From On-Premise to a Cloud-Native Architecture ... 240

7.2 ... Challenges of Legacy SAP BW Architectures ... 241

7.3 ... Role of Modernization in SAP Business Data Cloud ... 243

7.4 ... SAP Business Data Cloud Architecture for SAP BW Modernization ... 245

7.5 ... Transition Paths for SAP BW Modernization: Lift–Shift–Innovate Framework ... 247

7.6 ... Modernization Boundaries and Coexistence Models ... 263

7.7 ... Business Scenario: Transforming SAP BW into a Data Product–Driven Enterprise ... 266

7.8 ... Summary ... 270

8 ... Analytics and Planning with SAP Analytics Cloud ... 271

8.1 ... Role of SAP Analytics Cloud in the SAP Business Data Cloud Ecosystem ... 272

8.2 ... Architectural Building Blocks of SAP Analytics Cloud ... 273

8.3 ... Data Connectivity and Modeling ... 275

8.4 ... Analytics and Story Design ... 284

8.5 ... Planning and Forecasting ... 290

8.6 ... Augmented Analytics and AI ... 298

8.7 ... Security, Governance, and Collaboration ... 301

8.8 ... Design Best Practices for SAP Analytics Cloud ... 306

8.9 ... Business Scenario: From Data Product to Strategic Decision ... 310

8.10 ... Summary ... 313

9 ... Delivering Business Value with Intelligent Applications ... 315

9.1 ... Intelligent Applications in SAP Business Data Cloud ... 315

9.2 ... Business Value and Strategic Benefits of Intelligent Applications ... 318

9.3 ... Intelligent Application Architecture ... 320

9.4 ... Installing SAP-Managed Intelligent Applications ... 324

9.5 ... Extending and Customizing Intelligent Applications ... 331

9.6 ... Intelligent Applications Across Lines of Business ... 337

9.7 ... Business Scenario: Enhancing a Finance Intelligence Application ... 341

9.8 ... Summary ... 345

10 ... Adoption, Governance, and the Future of SAP Business Data Cloud ... 347

10.1 ... Adoption Patterns for SAP Business Data Cloud ... 348

10.2 ... Governance Principles in a Business Data Fabric ... 352

10.3 ... Operating Models for Data Product Ownership ... 355

10.4 ... Organizational Readiness and Role Evolution ... 358

10.5 ... Future Direction of SAP Business Data Cloud ... 362

10.6 ... Summary ... 364

... The Author ... 365

... Index ... 367

Über Autor(innen)

Bobbili, Geetha Madhuri
Geetha Madhuri Bobbili is an SAP data and analytics senior manager at Deloitte India. She has more than 12 years of experience with helping global enterprises modernize their analytics ecosystems and transform decision making. She has deep expertise in SAP BW/4HANA, native SAP HANA, SAP Analytics Cloud, SAP Datasphere, and SAP Cloud Integration for data services, with a strong track record of designing and governing enterprise-grade data integration and analytics architectures across hybrid landscapes.She is also a passionate educator and has authored numerous blog posts on SAP Datasphere, SAP Analytics Cloud, SAP HANA smart data integration, SAP Cloud Integration for data services, and more. Her blog posts have garnered a readership of over 90,000 professionals in the SAP community.